Feature: invoice ocr assistant

metagpt/actions/invoice_ocr.py

@@ -0,0 +1,223 @@
+#!/usr/bin/env python3
+# _*_ coding: utf-8 _*_
+
+"""
+@Time    : 2023/9/21 18:10:20
+@Author  : Stitch-z
+@File    : invoice_ocr.py
+@Describe : Actions of the invoice ocr assistant.
+"""
+
+import os
+import zipfile
+from enum import Enum
+from pathlib import Path
+
+import pandas as pd
+
+from typing import Dict, List
+from paddleocr import PaddleOCR
+
+from metagpt.actions import Action
+from metagpt.const import INVOICE_OCR_TABLE_PATH
+from metagpt.logs import logger
+from metagpt.prompts.invoice_ocr import EXTRACT_OCR_MAIN_INFO_PROMPT, REPLY_OCR_QUESTION_PROMPT
+from metagpt.utils.common import OutputParser
+from metagpt.utils.file import File
+
+
+class FileExtensionType(Enum):
+    """Enum representing file extensions and their associated types.
+    Each enum member consists of a tuple containing the file extension and its associated type.
+
+    """
+
+    ZIP = (".zip", "zip")
+    PDF = (".pdf", "pdf")
+    PNG = (".png", "png")
+    JPG = (".jpg", "jpg")
+
+    @classmethod
+    def get_extension_list(cls) -> List[str]:
+        """Get a list of file extensions.
+
+        Returns:
+            A list of file extensions as strings.
+        """
+        return [ext.value[0] for ext in cls]
+
+    @classmethod
+    def get_type_list(cls) -> List[str]:
+        """Get a list of file types.
+
+        Returns:
+            A list of file types as strings.
+        """
+        return [ext.value[1] for ext in cls]
+
+
+class InvoiceOCR(Action):
+    """Action class for performing OCR on invoice files, including zip, PDF, png, and jpg files.
+
+    Args:
+        name: The name of the action. Defaults to an empty string.
+        language: The language for OCR output. Defaults to "ch" (Chinese).
+
+    """
+
+    def __init__(self, name: str = "", *args, **kwargs):
+        super().__init__(name, *args, **kwargs)
+
+    @staticmethod
+    async def _check_file_type(filename: str) -> str:
+        """Check the file type of the given filename.
+
+        Args:
+            filename: The name of the file.
+
+        Returns:
+            The file type based on FileExtensionType enum.
+
+        Raises:
+            Exception: If the file format is not zip, pdf, png, or jpg.
+        """
+        file_ext = None
+        for ext in FileExtensionType:
+            if filename.endswith(ext.value[0]):
+                file_ext = ext.value[1]
+                break
+
+        if not file_ext:
+            raise Exception("The invoice format is not zip, pdf, png, or jpg")
+
+        return file_ext
+
+    @staticmethod
+    async def _unzip(file_path: Path) -> Path:
+        """Unzip a file and return the path to the unzipped directory.
+
+        Args:
+            file_path: The path to the zip file.
+
+        Returns:
+            The path to the unzipped directory.
+        """
+        file_directory = file_path.parent
+        with zipfile.ZipFile(file_path, 'r') as zip_ref:
+            for zip_info in zip_ref.infolist():
+                # Use CP437 to encode the file name, and then use GBK decoding to prevent Chinese garbled code
+                relative_name = zip_info.filename.encode('cp437').decode('gbk')
+                unzip_dir, name = relative_name.split("/")
+                if name:
+                    full_filename = file_directory / relative_name
+                    await File.write(full_filename.parent, name, zip_ref.read(zip_info.filename))
+
+        unzip_path = file_directory / unzip_dir
+        logger.info(f"unzip_path: {unzip_path}")
+        return unzip_path
+
+    async def run(self, file_path: Path, filename: str, *args, **kwargs) -> list:
+        """Execute the action to identify invoice files through OCR.
+
+        Args:
+            file_path: The path to the input file.
+            filename: The name of the input file.
+
+        Returns:
+            A list of OCR results.
+        """
+        file_ext = await self._check_file_type(filename)
+
+        if file_ext == FileExtensionType.ZIP.value[1]:
+            # OCR recognizes zip batch files
+            unzip_path = await self._unzip(file_path)
+            file_list = os.listdir(unzip_path)
+            ocr_list = []
+
+            for filename in file_list:
+                invoice_file_path = unzip_path / filename
+                # Identify files that match the type
+                if filename.split(".")[-1] in FileExtensionType.get_type_list():
+                    ocr = PaddleOCR(use_angle_cls=True, lang="ch", page_num=1)
+                    ocr_result = ocr.ocr(str(invoice_file_path), cls=True)
+                    ocr_list.append(ocr_result)
+            return ocr_list
+
+        else:
+            #  OCR identifies single file
+            ocr = PaddleOCR(use_angle_cls=True, lang="ch", page_num=1)
+            ocr_result = ocr.ocr(str(file_path), cls=True)
+            return [ocr_result]
+
+
+class GenerateTable(Action):
+    """Action class for generating tables from OCR results.
+
+    Args:
+        name: The name of the action. Defaults to an empty string.
+        language: The language used for the generated table. Defaults to "ch" (Chinese).
+
+    """
+
+    def __init__(self, name: str = "", language: str = "ch", *args, **kwargs):
+        super().__init__(name, *args, **kwargs)
+        self.language = language
+
+    async def run(self, ocr_results: list, filename: str, *args, **kwargs) -> Dict[str, str]:
+        """Processes OCR results, extracts invoice information, generates a table, and saves it as an Excel file.
+
+        Args:
+            ocr_results: A list of OCR results obtained from invoice processing.
+            filename: The name of the output Excel file.
+
+        Returns:
+            A dictionary containing the invoice information.
+
+        """
+        table_data = []
+        pathname = INVOICE_OCR_TABLE_PATH
+        pathname.mkdir(parents=True, exist_ok=True)
+
+        for ocr_result in ocr_results:
+            # Extract invoice OCR main information
+            prompt = EXTRACT_OCR_MAIN_INFO_PROMPT.format(ocr_result=ocr_result, language=self.language)
+            ocr_info = await self._aask(prompt=prompt)
+            invoice_data = OutputParser.extract_struct(ocr_info, dict)
+            if invoice_data:
+                table_data.append(invoice_data)
+
+        # Generate Excel file
+        filename = f"{filename.split('.')[0]}.xlsx"
+        full_filename = f"{pathname}/{filename}"
+        df = pd.DataFrame(table_data)
+        df.to_excel(full_filename, index=False)
+        return table_data
+
+
+class ReplyQuestion(Action):
+    """Action class for generating replies to questions based on OCR results.
+
+    Args:
+        name: The name of the action. Defaults to an empty string.
+        language: The language used for generating the reply. Defaults to "ch" (Chinese).
+
+    """
+
+    def __init__(self, name: str = "", language: str = "ch", *args, **kwargs):
+        super().__init__(name, *args, **kwargs)
+        self.language = language
+
+    async def run(self, query: str, ocr_result: list, *args, **kwargs) -> str:
+        """Reply to questions based on ocr results.
+
+        Args:
+            query: The question for which a reply is generated.
+            ocr_result: A list of OCR results.
+
+        Returns:
+            A reply result of string type.
+        """
+        prompt = REPLY_OCR_QUESTION_PROMPT.format(query=query, ocr_result=ocr_result, language=self.language)
+        resp = await self._aask(prompt=prompt)
+        return resp
+

metagpt/const.py

@@ -36,6 +36,7 @@ YAPI_URL = "http://yapi.deepwisdomai.com/"
 TMP = PROJECT_ROOT / "tmp"
 RESEARCH_PATH = DATA_PATH / "research"
 TUTORIAL_PATH = DATA_PATH / "tutorial_docx"
+INVOICE_OCR_TABLE_PATH = DATA_PATH / "invoice_table"
 
 SKILL_DIRECTORY = PROJECT_ROOT / "metagpt/skills"
 

metagpt/prompts/invoice_ocr.py

@@ -0,0 +1,39 @@
+#!/usr/bin/env python3
+# _*_ coding: utf-8 _*_
+
+"""
+@Time    : 2023/9/21 16:30:25
+@Author  : Stitch-z
+@File    : invoice_ocr.py
+@Describe : Prompts of the invoice ocr assistant.
+"""
+
+COMMON_PROMPT = "Now I will provide you with the OCR text recognition results for the invoice."
+
+EXTRACT_OCR_MAIN_INFO_PROMPT = COMMON_PROMPT + """
+Please extract the payee, city, total cost, and invoicing date of the invoice.
+
+The OCR data of the invoice are as follows:
+{ocr_result}
+
+Mandatory restrictions are returned according to the following requirements:
+1. The total cost refers to the total price and tax. Do not include `¥`.
+2. The city must be the recipient's city.
+2. The returned JSON dictionary must be returned in {language}
+3. Mandatory requirement to output in JSON format: {{"收款人":"x","城市":"x","总费用/元":"","开票日期":""}}.
+"""
+
+REPLY_OCR_QUESTION_PROMPT = COMMON_PROMPT + """
+Please answer the question: {query}
+
+The OCR data of the invoice are as follows:
+{ocr_result}
+
+Mandatory restrictions are returned according to the following requirements:
+1. Answer in {language} language.
+2. Enforce restrictions on not returning OCR data sent to you.
+3. Return with markdown syntax layout.
+"""
+
+INVOICE_OCR_SUCCESS = "Successfully completed OCR text recognition invoice."
+

metagpt/roles/invoice_ocr_assistant.py

@@ -0,0 +1,112 @@
+#!/usr/bin/env python3
+# _*_ coding: utf-8 _*_
+
+"""
+@Time    : 2023/9/21 14:10:05
+@Author  : Stitch-z
+@File    : invoice_ocr_assistant.py
+"""
+
+import os
+from pathlib import Path
+
+import pandas as pd
+from metagpt.actions.invoice_ocr import InvoiceOCR, GenerateTable, ReplyQuestion
+from metagpt.prompts.invoice_ocr import INVOICE_OCR_SUCCESS
+from metagpt.roles import Role
+from metagpt.schema import Message
+
+
+class InvoiceOCRAssistant(Role):
+    """Invoice OCR assistant, support OCR text recognition of invoice PDF, png, jpg, and zip files,
+    generate a table for the payee, city, total amount, and invoicing date of the invoice,
+    and ask questions for a single file based on the OCR recognition results of the invoice.
+
+    Args:
+        name: The name of the role.
+        profile: The role profile description.
+        goal: The goal of the role.
+        constraints: Constraints or requirements for the role.
+        language: The language in which the invoice table will be generated.
+    """
+
+    def __init__(
+        self,
+        name: str = "Stitch",
+        profile: str = "Invoice Ocr Assistant",
+        goal: str = "OCR identifies invoice files and generates invoice main information table",
+        constraints: str = "",
+        language: str = "ch",
+    ):
+        super().__init__(name, profile, goal, constraints)
+        self._init_actions([InvoiceOCR])
+        self.language = language
+        self.filename = ""
+        self.origin_query = ""
+        self.orc_data = None
+
+    async def _think(self) -> None:
+        """Determine the next action to be taken by the role."""
+        if self._rc.todo is None:
+            self._set_state(0)
+            return
+
+        if self._rc.state + 1 < len(self._states):
+            self._set_state(self._rc.state + 1)
+        else:
+            self._rc.todo = None
+
+    async def _act(self) -> Message:
+        """Perform an action as determined by the role.
+
+        Returns:
+            A message containing the result of the action.
+        """
+        msg = self._rc.memory.get(k=1)[0]
+        todo = self._rc.todo
+        if isinstance(todo, InvoiceOCR):
+            self.origin_query = msg.content
+            file_path = msg.instruct_content.get("file_path")
+            self.filename = os.path.basename(file_path)
+            if not file_path:
+                raise Exception("Invoice file not uploaded")
+
+            resp = await todo.run(Path(file_path), self.filename)
+            if len(resp) == 1:
+                # Single file support for questioning based on OCR recognition results
+                self._init_actions([GenerateTable, ReplyQuestion])
+                self.orc_data = resp[0]
+            else:
+                self._init_actions([GenerateTable])
+
+            self._rc.todo = None
+            content = INVOICE_OCR_SUCCESS
+        elif isinstance(todo, GenerateTable):
+            ocr_results = msg.instruct_content
+            resp = await todo.run(ocr_results, self.filename)
+
+            # Convert list to Markdown format string
+            df = pd.DataFrame(resp)
+            markdown_table = df.to_markdown(index=False)
+            content = f"{markdown_table}\n\n\n"
+        else:
+            resp = await todo.run(self.origin_query, self.orc_data)
+            content = resp
+
+        msg = Message(content=content, instruct_content=resp)
+        self._rc.memory.add(msg)
+        return msg
+
+    async def _react(self) -> Message:
+        """Execute the invoice ocr assistant's think and actions.
+
+        Returns:
+            A message containing the final result of the assistant's actions.
+        """
+        while True:
+            await self._think()
+            if self._rc.todo is None:
+                break
+            msg = await self._act()
+        return msg
+

metagpt/utils/common.py

@@ -195,7 +195,8 @@ class OutputParser:
             except (ValueError, SyntaxError) as e:
                 raise Exception(f"Error while extracting and parsing the {data_type}: {e}")
         else:
-            raise Exception(f"No {data_type} found in the text.")
+            logger.error(f"No {data_type} found in the text.")
+            return [] if data_type is list else {}
 
 
 class CodeParser: